{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 监督模型"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "import datetime\n",
    "\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "一.数据预处理"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Time</th>\n",
       "      <th>V1</th>\n",
       "      <th>V2</th>\n",
       "      <th>V3</th>\n",
       "      <th>V4</th>\n",
       "      <th>V5</th>\n",
       "      <th>V6</th>\n",
       "      <th>V7</th>\n",
       "      <th>V8</th>\n",
       "      <th>V9</th>\n",
       "      <th>...</th>\n",
       "      <th>V21</th>\n",
       "      <th>V22</th>\n",
       "      <th>V23</th>\n",
       "      <th>V24</th>\n",
       "      <th>V25</th>\n",
       "      <th>V26</th>\n",
       "      <th>V27</th>\n",
       "      <th>V28</th>\n",
       "      <th>Amount</th>\n",
       "      <th>Class</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.0</td>\n",
       "      <td>-1.359807</td>\n",
       "      <td>-0.072781</td>\n",
       "      <td>2.536347</td>\n",
       "      <td>1.378155</td>\n",
       "      <td>-0.338321</td>\n",
       "      <td>0.462388</td>\n",
       "      <td>0.239599</td>\n",
       "      <td>0.098698</td>\n",
       "      <td>0.363787</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.018307</td>\n",
       "      <td>0.277838</td>\n",
       "      <td>-0.110474</td>\n",
       "      <td>0.066928</td>\n",
       "      <td>0.128539</td>\n",
       "      <td>-0.189115</td>\n",
       "      <td>0.133558</td>\n",
       "      <td>-0.021053</td>\n",
       "      <td>149.62</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.0</td>\n",
       "      <td>1.191857</td>\n",
       "      <td>0.266151</td>\n",
       "      <td>0.166480</td>\n",
       "      <td>0.448154</td>\n",
       "      <td>0.060018</td>\n",
       "      <td>-0.082361</td>\n",
       "      <td>-0.078803</td>\n",
       "      <td>0.085102</td>\n",
       "      <td>-0.255425</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.225775</td>\n",
       "      <td>-0.638672</td>\n",
       "      <td>0.101288</td>\n",
       "      <td>-0.339846</td>\n",
       "      <td>0.167170</td>\n",
       "      <td>0.125895</td>\n",
       "      <td>-0.008983</td>\n",
       "      <td>0.014724</td>\n",
       "      <td>2.69</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1.0</td>\n",
       "      <td>-1.358354</td>\n",
       "      <td>-1.340163</td>\n",
       "      <td>1.773209</td>\n",
       "      <td>0.379780</td>\n",
       "      <td>-0.503198</td>\n",
       "      <td>1.800499</td>\n",
       "      <td>0.791461</td>\n",
       "      <td>0.247676</td>\n",
       "      <td>-1.514654</td>\n",
       "      <td>...</td>\n",
       "      <td>0.247998</td>\n",
       "      <td>0.771679</td>\n",
       "      <td>0.909412</td>\n",
       "      <td>-0.689281</td>\n",
       "      <td>-0.327642</td>\n",
       "      <td>-0.139097</td>\n",
       "      <td>-0.055353</td>\n",
       "      <td>-0.059752</td>\n",
       "      <td>378.66</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1.0</td>\n",
       "      <td>-0.966272</td>\n",
       "      <td>-0.185226</td>\n",
       "      <td>1.792993</td>\n",
       "      <td>-0.863291</td>\n",
       "      <td>-0.010309</td>\n",
       "      <td>1.247203</td>\n",
       "      <td>0.237609</td>\n",
       "      <td>0.377436</td>\n",
       "      <td>-1.387024</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.108300</td>\n",
       "      <td>0.005274</td>\n",
       "      <td>-0.190321</td>\n",
       "      <td>-1.175575</td>\n",
       "      <td>0.647376</td>\n",
       "      <td>-0.221929</td>\n",
       "      <td>0.062723</td>\n",
       "      <td>0.061458</td>\n",
       "      <td>123.50</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2.0</td>\n",
       "      <td>-1.158233</td>\n",
       "      <td>0.877737</td>\n",
       "      <td>1.548718</td>\n",
       "      <td>0.403034</td>\n",
       "      <td>-0.407193</td>\n",
       "      <td>0.095921</td>\n",
       "      <td>0.592941</td>\n",
       "      <td>-0.270533</td>\n",
       "      <td>0.817739</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.009431</td>\n",
       "      <td>0.798278</td>\n",
       "      <td>-0.137458</td>\n",
       "      <td>0.141267</td>\n",
       "      <td>-0.206010</td>\n",
       "      <td>0.502292</td>\n",
       "      <td>0.219422</td>\n",
       "      <td>0.215153</td>\n",
       "      <td>69.99</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 31 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   Time        V1        V2        V3        V4        V5        V6        V7  \\\n",
       "0   0.0 -1.359807 -0.072781  2.536347  1.378155 -0.338321  0.462388  0.239599   \n",
       "1   0.0  1.191857  0.266151  0.166480  0.448154  0.060018 -0.082361 -0.078803   \n",
       "2   1.0 -1.358354 -1.340163  1.773209  0.379780 -0.503198  1.800499  0.791461   \n",
       "3   1.0 -0.966272 -0.185226  1.792993 -0.863291 -0.010309  1.247203  0.237609   \n",
       "4   2.0 -1.158233  0.877737  1.548718  0.403034 -0.407193  0.095921  0.592941   \n",
       "\n",
       "         V8        V9  ...         V21       V22       V23       V24  \\\n",
       "0  0.098698  0.363787  ...   -0.018307  0.277838 -0.110474  0.066928   \n",
       "1  0.085102 -0.255425  ...   -0.225775 -0.638672  0.101288 -0.339846   \n",
       "2  0.247676 -1.514654  ...    0.247998  0.771679  0.909412 -0.689281   \n",
       "3  0.377436 -1.387024  ...   -0.108300  0.005274 -0.190321 -1.175575   \n",
       "4 -0.270533  0.817739  ...   -0.009431  0.798278 -0.137458  0.141267   \n",
       "\n",
       "        V25       V26       V27       V28  Amount  Class  \n",
       "0  0.128539 -0.189115  0.133558 -0.021053  149.62      0  \n",
       "1  0.167170  0.125895 -0.008983  0.014724    2.69      0  \n",
       "2 -0.327642 -0.139097 -0.055353 -0.059752  378.66      0  \n",
       "3  0.647376 -0.221929  0.062723  0.061458  123.50      0  \n",
       "4 -0.206010  0.502292  0.219422  0.215153   69.99      0  \n",
       "\n",
       "[5 rows x 31 columns]"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Data = pd.read_csv(r\"C:/ML/creditcard.csv\")\n",
    "Data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<style>\n",
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       "\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Time</th>\n",
       "      <th>V1</th>\n",
       "      <th>V2</th>\n",
       "      <th>V3</th>\n",
       "      <th>V4</th>\n",
       "      <th>V5</th>\n",
       "      <th>V6</th>\n",
       "      <th>V7</th>\n",
       "      <th>V8</th>\n",
       "      <th>V9</th>\n",
       "      <th>...</th>\n",
       "      <th>V21</th>\n",
       "      <th>V22</th>\n",
       "      <th>V23</th>\n",
       "      <th>V24</th>\n",
       "      <th>V25</th>\n",
       "      <th>V26</th>\n",
       "      <th>V27</th>\n",
       "      <th>V28</th>\n",
       "      <th>Amount</th>\n",
       "      <th>Class</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>284807.000000</td>\n",
       "      <td>2.848070e+05</td>\n",
       "      <td>2.848070e+05</td>\n",
       "      <td>2.848070e+05</td>\n",
       "      <td>2.848070e+05</td>\n",
       "      <td>2.848070e+05</td>\n",
       "      <td>2.848070e+05</td>\n",
       "      <td>2.848070e+05</td>\n",
       "      <td>2.848070e+05</td>\n",
       "      <td>2.848070e+05</td>\n",
       "      <td>...</td>\n",
       "      <td>2.848070e+05</td>\n",
       "      <td>2.848070e+05</td>\n",
       "      <td>2.848070e+05</td>\n",
       "      <td>2.848070e+05</td>\n",
       "      <td>2.848070e+05</td>\n",
       "      <td>2.848070e+05</td>\n",
       "      <td>2.848070e+05</td>\n",
       "      <td>2.848070e+05</td>\n",
       "      <td>284807.000000</td>\n",
       "      <td>284807.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>94813.859575</td>\n",
       "      <td>3.919560e-15</td>\n",
       "      <td>5.688174e-16</td>\n",
       "      <td>-8.769071e-15</td>\n",
       "      <td>2.782312e-15</td>\n",
       "      <td>-1.552563e-15</td>\n",
       "      <td>2.010663e-15</td>\n",
       "      <td>-1.694249e-15</td>\n",
       "      <td>-1.927028e-16</td>\n",
       "      <td>-3.137024e-15</td>\n",
       "      <td>...</td>\n",
       "      <td>1.537294e-16</td>\n",
       "      <td>7.959909e-16</td>\n",
       "      <td>5.367590e-16</td>\n",
       "      <td>4.458112e-15</td>\n",
       "      <td>1.453003e-15</td>\n",
       "      <td>1.699104e-15</td>\n",
       "      <td>-3.660161e-16</td>\n",
       "      <td>-1.206049e-16</td>\n",
       "      <td>88.349619</td>\n",
       "      <td>0.001727</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>47488.145955</td>\n",
       "      <td>1.958696e+00</td>\n",
       "      <td>1.651309e+00</td>\n",
       "      <td>1.516255e+00</td>\n",
       "      <td>1.415869e+00</td>\n",
       "      <td>1.380247e+00</td>\n",
       "      <td>1.332271e+00</td>\n",
       "      <td>1.237094e+00</td>\n",
       "      <td>1.194353e+00</td>\n",
       "      <td>1.098632e+00</td>\n",
       "      <td>...</td>\n",
       "      <td>7.345240e-01</td>\n",
       "      <td>7.257016e-01</td>\n",
       "      <td>6.244603e-01</td>\n",
       "      <td>6.056471e-01</td>\n",
       "      <td>5.212781e-01</td>\n",
       "      <td>4.822270e-01</td>\n",
       "      <td>4.036325e-01</td>\n",
       "      <td>3.300833e-01</td>\n",
       "      <td>250.120109</td>\n",
       "      <td>0.041527</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>-5.640751e+01</td>\n",
       "      <td>-7.271573e+01</td>\n",
       "      <td>-4.832559e+01</td>\n",
       "      <td>-5.683171e+00</td>\n",
       "      <td>-1.137433e+02</td>\n",
       "      <td>-2.616051e+01</td>\n",
       "      <td>-4.355724e+01</td>\n",
       "      <td>-7.321672e+01</td>\n",
       "      <td>-1.343407e+01</td>\n",
       "      <td>...</td>\n",
       "      <td>-3.483038e+01</td>\n",
       "      <td>-1.093314e+01</td>\n",
       "      <td>-4.480774e+01</td>\n",
       "      <td>-2.836627e+00</td>\n",
       "      <td>-1.029540e+01</td>\n",
       "      <td>-2.604551e+00</td>\n",
       "      <td>-2.256568e+01</td>\n",
       "      <td>-1.543008e+01</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>54201.500000</td>\n",
       "      <td>-9.203734e-01</td>\n",
       "      <td>-5.985499e-01</td>\n",
       "      <td>-8.903648e-01</td>\n",
       "      <td>-8.486401e-01</td>\n",
       "      <td>-6.915971e-01</td>\n",
       "      <td>-7.682956e-01</td>\n",
       "      <td>-5.540759e-01</td>\n",
       "      <td>-2.086297e-01</td>\n",
       "      <td>-6.430976e-01</td>\n",
       "      <td>...</td>\n",
       "      <td>-2.283949e-01</td>\n",
       "      <td>-5.423504e-01</td>\n",
       "      <td>-1.618463e-01</td>\n",
       "      <td>-3.545861e-01</td>\n",
       "      <td>-3.171451e-01</td>\n",
       "      <td>-3.269839e-01</td>\n",
       "      <td>-7.083953e-02</td>\n",
       "      <td>-5.295979e-02</td>\n",
       "      <td>5.600000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>84692.000000</td>\n",
       "      <td>1.810880e-02</td>\n",
       "      <td>6.548556e-02</td>\n",
       "      <td>1.798463e-01</td>\n",
       "      <td>-1.984653e-02</td>\n",
       "      <td>-5.433583e-02</td>\n",
       "      <td>-2.741871e-01</td>\n",
       "      <td>4.010308e-02</td>\n",
       "      <td>2.235804e-02</td>\n",
       "      <td>-5.142873e-02</td>\n",
       "      <td>...</td>\n",
       "      <td>-2.945017e-02</td>\n",
       "      <td>6.781943e-03</td>\n",
       "      <td>-1.119293e-02</td>\n",
       "      <td>4.097606e-02</td>\n",
       "      <td>1.659350e-02</td>\n",
       "      <td>-5.213911e-02</td>\n",
       "      <td>1.342146e-03</td>\n",
       "      <td>1.124383e-02</td>\n",
       "      <td>22.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>139320.500000</td>\n",
       "      <td>1.315642e+00</td>\n",
       "      <td>8.037239e-01</td>\n",
       "      <td>1.027196e+00</td>\n",
       "      <td>7.433413e-01</td>\n",
       "      <td>6.119264e-01</td>\n",
       "      <td>3.985649e-01</td>\n",
       "      <td>5.704361e-01</td>\n",
       "      <td>3.273459e-01</td>\n",
       "      <td>5.971390e-01</td>\n",
       "      <td>...</td>\n",
       "      <td>1.863772e-01</td>\n",
       "      <td>5.285536e-01</td>\n",
       "      <td>1.476421e-01</td>\n",
       "      <td>4.395266e-01</td>\n",
       "      <td>3.507156e-01</td>\n",
       "      <td>2.409522e-01</td>\n",
       "      <td>9.104512e-02</td>\n",
       "      <td>7.827995e-02</td>\n",
       "      <td>77.165000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>172792.000000</td>\n",
       "      <td>2.454930e+00</td>\n",
       "      <td>2.205773e+01</td>\n",
       "      <td>9.382558e+00</td>\n",
       "      <td>1.687534e+01</td>\n",
       "      <td>3.480167e+01</td>\n",
       "      <td>7.330163e+01</td>\n",
       "      <td>1.205895e+02</td>\n",
       "      <td>2.000721e+01</td>\n",
       "      <td>1.559499e+01</td>\n",
       "      <td>...</td>\n",
       "      <td>2.720284e+01</td>\n",
       "      <td>1.050309e+01</td>\n",
       "      <td>2.252841e+01</td>\n",
       "      <td>4.584549e+00</td>\n",
       "      <td>7.519589e+00</td>\n",
       "      <td>3.517346e+00</td>\n",
       "      <td>3.161220e+01</td>\n",
       "      <td>3.384781e+01</td>\n",
       "      <td>25691.160000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>8 rows × 31 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                Time            V1            V2            V3            V4  \\\n",
       "count  284807.000000  2.848070e+05  2.848070e+05  2.848070e+05  2.848070e+05   \n",
       "mean    94813.859575  3.919560e-15  5.688174e-16 -8.769071e-15  2.782312e-15   \n",
       "std     47488.145955  1.958696e+00  1.651309e+00  1.516255e+00  1.415869e+00   \n",
       "min         0.000000 -5.640751e+01 -7.271573e+01 -4.832559e+01 -5.683171e+00   \n",
       "25%     54201.500000 -9.203734e-01 -5.985499e-01 -8.903648e-01 -8.486401e-01   \n",
       "50%     84692.000000  1.810880e-02  6.548556e-02  1.798463e-01 -1.984653e-02   \n",
       "75%    139320.500000  1.315642e+00  8.037239e-01  1.027196e+00  7.433413e-01   \n",
       "max    172792.000000  2.454930e+00  2.205773e+01  9.382558e+00  1.687534e+01   \n",
       "\n",
       "                 V5            V6            V7            V8            V9  \\\n",
       "count  2.848070e+05  2.848070e+05  2.848070e+05  2.848070e+05  2.848070e+05   \n",
       "mean  -1.552563e-15  2.010663e-15 -1.694249e-15 -1.927028e-16 -3.137024e-15   \n",
       "std    1.380247e+00  1.332271e+00  1.237094e+00  1.194353e+00  1.098632e+00   \n",
       "min   -1.137433e+02 -2.616051e+01 -4.355724e+01 -7.321672e+01 -1.343407e+01   \n",
       "25%   -6.915971e-01 -7.682956e-01 -5.540759e-01 -2.086297e-01 -6.430976e-01   \n",
       "50%   -5.433583e-02 -2.741871e-01  4.010308e-02  2.235804e-02 -5.142873e-02   \n",
       "75%    6.119264e-01  3.985649e-01  5.704361e-01  3.273459e-01  5.971390e-01   \n",
       "max    3.480167e+01  7.330163e+01  1.205895e+02  2.000721e+01  1.559499e+01   \n",
       "\n",
       "           ...                 V21           V22           V23           V24  \\\n",
       "count      ...        2.848070e+05  2.848070e+05  2.848070e+05  2.848070e+05   \n",
       "mean       ...        1.537294e-16  7.959909e-16  5.367590e-16  4.458112e-15   \n",
       "std        ...        7.345240e-01  7.257016e-01  6.244603e-01  6.056471e-01   \n",
       "min        ...       -3.483038e+01 -1.093314e+01 -4.480774e+01 -2.836627e+00   \n",
       "25%        ...       -2.283949e-01 -5.423504e-01 -1.618463e-01 -3.545861e-01   \n",
       "50%        ...       -2.945017e-02  6.781943e-03 -1.119293e-02  4.097606e-02   \n",
       "75%        ...        1.863772e-01  5.285536e-01  1.476421e-01  4.395266e-01   \n",
       "max        ...        2.720284e+01  1.050309e+01  2.252841e+01  4.584549e+00   \n",
       "\n",
       "                V25           V26           V27           V28         Amount  \\\n",
       "count  2.848070e+05  2.848070e+05  2.848070e+05  2.848070e+05  284807.000000   \n",
       "mean   1.453003e-15  1.699104e-15 -3.660161e-16 -1.206049e-16      88.349619   \n",
       "std    5.212781e-01  4.822270e-01  4.036325e-01  3.300833e-01     250.120109   \n",
       "min   -1.029540e+01 -2.604551e+00 -2.256568e+01 -1.543008e+01       0.000000   \n",
       "25%   -3.171451e-01 -3.269839e-01 -7.083953e-02 -5.295979e-02       5.600000   \n",
       "50%    1.659350e-02 -5.213911e-02  1.342146e-03  1.124383e-02      22.000000   \n",
       "75%    3.507156e-01  2.409522e-01  9.104512e-02  7.827995e-02      77.165000   \n",
       "max    7.519589e+00  3.517346e+00  3.161220e+01  3.384781e+01   25691.160000   \n",
       "\n",
       "               Class  \n",
       "count  284807.000000  \n",
       "mean        0.001727  \n",
       "std         0.041527  \n",
       "min         0.000000  \n",
       "25%         0.000000  \n",
       "50%         0.000000  \n",
       "75%         0.000000  \n",
       "max         1.000000  \n",
       "\n",
       "[8 rows x 31 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Data.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "检查是否有缺失值"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Data.isnull().any().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "利用heatmap来分析特征之间的相关度"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1487202ae10>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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7z9Hjprbcfhurcst45MXWdQU4cOIOLbe/ui//71JfgUmXx+f8s1tTwfDOIs1T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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x148720347f0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.heatmap(Data.corr())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "总体来看V1-V28特征之间的相关度非常小，这可能是由于这些数据是由原始数据经过PCA处理导致的，相关度低的特征对于之后的训练模型比较有利"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "通过可视化样本的标签可以发现样本严重不平衡，符合现实的场景就是欺诈的数目只占样本的极小的一部分,样本如此偏斜的分布的处理十分关键"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5,1,'Class Distributions \\n (0: Not Fraud  1: Fraud)')"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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kLZZ0l6TjcvmXJD0gaWF+HFLZ52RJHZLulnRQpXxCLuuQdFKlfBdJv5O0RNKPJW2Ry5+X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\nKSWq3QAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1486e216358>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot('Class', data=Data)\n",
    "plt.title('Class Distributions \\n (0: Not Fraud  1: Fraud)', fontsize=14)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "可视化各个特征与样本是否属于欺诈样本的关系"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.PairGrid at 0x148051a2278>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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krZGkJUuWzLxlwNTUNcNdHTl1tue0dXfPqPKtu3vU1ZEbrhN9HhyVx+ufcty8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HCAzfoAu49Ad9oTfYyK3VLKi45EZw4VXdSGO1t/oeP0Wdtw16Y7nIdOZ8NQZMcd9TvqqP2Crte3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8vOQtff4c0CJwxBfV4oydAt1URYvcLvUzPkQHqfcxE9z/whrqTxjOwg+aixXtplab+2ZMVGrp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\nFybe+UyQKJeskiptS6SyJMpnlM/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JI6P9kEd8ET9Wg+eD3s3zjjCG9w57E6OV5jW/e3Ud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6mFhUW3JDVOGT+4D49MHYMQ0CffRW3VcEPnAGD2qs3MmjQy7bTWm+Uk2eOyZUyYt+72ce/z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7OiguZ+bXwaGN4LRAn4FoLMHAq9rTEIrhV8wb+MCr2hONJdIVPB2ubKyFWgs1R2Ih09C+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\nkUz4f6z2qGiqk25cAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x14805178ba8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.pairplot(Data.loc[:, ['Class', 'Amount', 'Time', 'V1', 'V2']], hue='Class')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "然后考察Amount，Time特征的偏斜程度。对于Amount，严重右偏，大多数情况下，交易总量会稳定在一个比较小的范围；对于Time特征可以发现，交易时间间隔存在着一些周期性。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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JxZNOgu99zxNU6axf7/M8VN5eftl7ZTzyiG8vKvLERaJGjeDII+GMM3yiy44d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\nEUktdVyIiIiIiIiISGr9PwTmbbI9+nKEAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x148068fc828>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(1, 2, figsize=(18,4))\n",
    "\n",
    "amount_val = Data['Amount'].values\n",
    "time_val = Data['Time'].values\n",
    "\n",
    "sns.distplot(amount_val, ax=ax[0], color='r')\n",
    "ax[0].set_title('Distribution of Transaction Amount', fontsize=14)\n",
    "ax[0].set_xlim([min(amount_val), max(amount_val)])\n",
    "\n",
    "sns.distplot(time_val, ax=ax[1], color='b')\n",
    "ax[1].set_title('Distribution of Transaction Time', fontsize=14)\n",
    "ax[1].set_xlim([min(time_val), max(time_val)])\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "可视化一下正常样本与欺诈样本的交易时间，Amount分布的不同"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5,1,'Transaction time distribution - normal and fraud')"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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omxA7jtuRiBSvSZNsJeihQ+0MjZIQGmqXRtx1F/z4I3TrBtu3l0zfIlI6KCEW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\ngg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x148068d4f60>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(16,9),)\n",
    "ax=sns.kdeplot(Data.loc[(Data['Class'] == 0), 'Time'] , color='b', shade=True,label='normal transaction')\n",
    "ax=sns.kdeplot(Data.loc[(Data['Class'] == 1), 'Time'] , color='r', shade=True, label='fraud transaction')\n",
    "plt.title('Transaction time distribution - normal and fraud')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x148051a2710>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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TijLPPP300w3nn39+YqptzjjjDOeRRx55obGx0TzzzDN111xzTdf+/fufv+uuu1a+8Y1v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\nGEYsZiQMwzCMWMxIGIZhGLH8P/QdddijuKCVAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x148046f3438>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.lmplot(x='Time', y='Amount', data=Data,\n",
    "           fit_reg=False, \n",
    "           hue='Class') "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "对于Amount和Time特征，由于它们的范围与其他特征相差太大，需要对它们进行缩放，由于样本中的异常值（欺诈样本）十分重要，因此采用对数据的中心和范围更稳健估计的RobustScaler"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\ana\\lib\\site-packages\\ipykernel_launcher.py:5: FutureWarning: reshape is deprecated and will raise in a subsequent release. Please use .values.reshape(...) instead\n",
      "  \"\"\"\n",
      "C:\\ana\\lib\\site-packages\\ipykernel_launcher.py:6: FutureWarning: reshape is deprecated and will raise in a subsequent release. Please use .values.reshape(...) instead\n",
      "  \n"
     ]
    }
   ],
   "source": [
    "from sklearn.preprocessing import StandardScaler, RobustScaler\n",
    "\n",
    "rob_scaler = RobustScaler()\n",
    "\n",
    "Data['scaled_amount'] = rob_scaler.fit_transform(Data['Amount'].reshape(-1,1))\n",
    "Data['scaled_time'] = rob_scaler.fit_transform(Data['Time'].reshape(-1,1))\n",
    "\n",
    "Data.drop(['Time','Amount'], axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "利用t-SNE降维之后，观察数据的分布"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\ana\\lib\\site-packages\\ipykernel_launcher.py:12: DeprecationWarning: \n",
      ".ix is deprecated. Please use\n",
      ".loc for label based indexing or\n",
      ".iloc for positional indexing\n",
      "\n",
      "See the documentation here:\n",
      "http://pandas.pydata.org/pandas-docs/stable/indexing.html#ix-indexer-is-deprecated\n",
      "  if sys.path[0] == '':\n"
     ]
    },
    {
     "data": {
      "image/png": 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KxXyP+t00xpj9wH7v++MicgdwWtZyS6Veh0sumTvXcHe37Rt3RZXTevjklczQ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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1482d497e10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn.manifold import TSNE\n",
    "\n",
    "Data2 = Data[Data.Class == 1]\n",
    "Data2 = pd.concat([Data2, Data[Data.Class == 0].sample(n = 10000)], axis = 0)\n",
    "\n",
    "y = Data2.ix[:,-1].values\n",
    "tsne = TSNE(n_components=2, random_state=0)\n",
    "x_2d = tsne.fit_transform(Data2)\n",
    "\n",
    "color_map = {0:'red', 1:'blue'}\n",
    "plt.figure(figsize=(16,9),)\n",
    "for idx, cl in enumerate(np.unique(y)):\n",
    "    plt.scatter(x = x_2d[y==cl,0], \n",
    "                y = x_2d[y==cl,1], \n",
    "                c = color_map[idx], \n",
    "                label = cl)\n",
    "plt.xlabel('X in t-SNE')\n",
    "plt.ylabel('Y in t-SNE')\n",
    "plt.legend(loc='upper left')\n",
    "plt.title('t-SNE visualization of data')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "利用统计学手段来分析欺诈样本Amount与总体样本Amount的关系，利用单样本t-检验，来检验欺诈样本的Amount的平均值与总体样本平均值是否显著不同"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "mean amount of population: 88.34961925087359, mean amount of fraud transaction: 122.21132113821133\n"
     ]
    }
   ],
   "source": [
    "amount_population = Data.Amount.mean()\n",
    "amount_fraud = Data[Data.Class == 1].Amount.mean()\n",
    "print('mean amount of population: {}, mean amount of fraud transaction: {}'.format(amount_population, amount_fraud))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Ttest_1sampResult(statistic=2.9261308240301198, pvalue=0.0035910854878476715)"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import scipy.stats as stats\n",
    "stats.ttest_1samp(a=Data[Data['Class']==1]['Amount'], popmean=amount_population)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The t-distribution left quartile range is: -1.96479735565\n",
      "The t-distribution right quartile range is: 1.96479735565\n"
     ]
    }
   ],
   "source": [
    "degree_freedom = len(Data[Data['Class']==1])\n",
    "conf_level = 0.95\n",
    "\n",
    "LQ = stats.t.ppf((1-conf_level)/2,degree_freedom)  \n",
    "\n",
    "RQ = stats.t.ppf((1+conf_level)/2,degree_freedom)  \n",
    "\n",
    "print ('The t-distribution left quartile range is: ' + str(LQ))\n",
    "print ('The t-distribution right quartile range is: ' + str(RQ))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "结果显示，在0.05显著度下，由于t值在95%置信区间范围外，我们可以拒绝原假设，可以认为欺诈样本Amount平均值与总体Amount平均值显著不同。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "为了得到一个更加平衡的数据集，将采用过采样的方试，使用了SMOTE算法。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "二.训练模型"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "利用StratifiedShuffleSplit划分数据集，使得各个数据集的样本比例大致相同"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from sklearn.model_selection import StratifiedShuffleSplit\n",
    "\n",
    "sss = StratifiedShuffleSplit(n_splits=1, test_size=0.2, random_state=5)\n",
    "X = Data.drop(['Class', 'scaled_time'], axis=1)\n",
    "X = rob_scaler.fit_transform(X.values)\n",
    "y = Data['Class'].values\n",
    "for train_index, test_index in sss.split(X, y):\n",
    "    X_train_ = X[train_index, :]\n",
    "    y_train_ = y[train_index]\n",
    "    X_test = X[test_index, :]\n",
    "    y_test = y[test_index]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from sklearn.metrics import roc_auc_score\n",
    "from sklearn.metrics import recall_score\n",
    "from sklearn.model_selection import StratifiedKFold\n",
    "\n",
    "def kfold_cv(Model, X, y, n_splits=10, smote=True, verbose=False):\n",
    "    \n",
    "    skf = StratifiedKFold(n_splits, random_state=5, shuffle=True)\n",
    "    C = np.logspace(-3, 3, num=7, base=10)\n",
    "    def sub_cv(model):\n",
    "        kfold = skf.split(X, y)\n",
    "        scores = 0\n",
    "        recall = 0\n",
    "        if smote:\n",
    "            sme = SMOTEENN(random_state=5)\n",
    "        i = 0\n",
    "        for train_index, test_index in kfold:\n",
    "            X_train_ = X[train_index, :]\n",
    "            y_train_ = y[train_index]\n",
    "            X_test = X[test_index, :]\n",
    "            y_test = y[test_index]\n",
    "            if smote:\n",
    "                X_train, y_train = sme.fit_sample(X_train_, y_train_)\n",
    "            else:\n",
    "                X_train = X_train_\n",
    "                y_train = y_train_\n",
    "            model.fit(X_train, y_train)\n",
    "            y_pred = model.predict(X_test)\n",
    "            y_score = model.predict_proba(X_test)[:, 1]\n",
    "            score = roc_auc_score(y_test, y_score, average='micro')\n",
    "            if verbose:\n",
    "                print('Trained {} th model, AUC score: {}'.format(i+1, score))\n",
    "            scores += score\n",
    "            recall += recall_score(y_test, y_pred)\n",
    "            i += 1\n",
    "        return scores / i, recall / i\n",
    "    bestC = 0\n",
    "    bestauc = 0\n",
    "    bestrecall = 0\n",
    "    for c in C:\n",
    "        model = Model(class_weight='balanced', C=c)\n",
    "        auc, recall = sub_cv(model)\n",
    "        if recall > bestrecall:\n",
    "            bestauc = auc\n",
    "            bestC = c\n",
    "            bestrecall = recall\n",
    "        print('C: {}, AUC: {}, recall: {}, best C: {}'.format(c, auc, recall, bestC))\n",
    "    return bestC, bestauc, bestrecall"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "C: 0.001, AUC: 0.9787654633632332, recall: 0.8985069782538136, best C: 0.001\n",
      "C: 0.01, AUC: 0.9785264739154946, recall: 0.9061019149626744, best C: 0.01\n",
      "C: 0.1, AUC: 0.9784538325337623, recall: 0.911165206101915, best C: 0.1\n",
      "C: 1.0, AUC: 0.978458451208998, recall: 0.911165206101915, best C: 0.1\n",
      "C: 10.0, AUC: 0.9784563677942872, recall: 0.911165206101915, best C: 0.1\n",
      "C: 100.0, AUC: 0.9784558266065467, recall: 0.911165206101915, best C: 0.1\n",
      "C: 1000.0, AUC: 0.9784558280347648, recall: 0.911165206101915, best C: 0.1\n",
      "Best C: 0.1\n"
     ]
    }
   ],
   "source": [
    "from sklearn.linear_model import LogisticRegression\n",
    "from sklearn.metrics import confusion_matrix\n",
    "from imblearn.combine import SMOTEENN \n",
    "\n",
    "Model = LogisticRegression\n",
    "bestC, bestauc, bestrecall = kfold_cv(Model, X_train_, y_train_, n_splits=5, verbose=False)\n",
    "print('Best C: {}'.format(bestC))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "AUC: 0.9771366410942544, recall: 0.9081632653061225\n"
     ]
    }
   ],
   "source": [
    "baseline = Model(class_weight='balanced', C=bestC)\n",
    "baseline.fit(X_train_, y_train_)\n",
    "y_pred = baseline.predict(X_test)\n",
    "y_score = baseline.predict_proba(X_test)[:, 1] #\n",
    "auc = roc_auc_score(y_test, y_score, average='micro')\n",
    "recall = recall_score(y_test, y_pred)\n",
    "print('AUC: {}, recall: {}'.format(auc, recall))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1482f3c0e10>"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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7duDMmV8A2L//MBYWFrzwwp/faWjUqCHNmzflwIHDBue1aaPR/0tAFELJU388hsDAQEaM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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1482f3c0860>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "cm=confusion_matrix(y_test, y_pred)\n",
    "df_cm = pd.DataFrame(cm,\n",
    "                  ['True Normal','True Fraud'],['Pred Normal','Pred Fraud'])\n",
    "\n",
    "sns.set(font_scale=1.4)\n",
    "sns.heatmap(df_cm, annot=True,annot_kws={\"size\": 16},fmt='g')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "改进：\n",
    "1.尝试Xgboost，lightgbm等树模型，模型调参\n",
    "2.尝试半监督的方法，例如半监督SVM（TSVM）\n",
    "3.基于现实，将问题转化为多分类问题，寻找欺诈样本中不同的模式\n",
    "4.无监督学习：密度聚类，Isolation Forest，多元高斯分布\n",
    "5.利用统计学方法分析欺诈样本的与正常样本有显著性差异的特征，并利用这些特征分析\n",
    "6.尝试欠采样方法，利用Easy ensemble方法"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
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